Changes in Accelerometer-Measured Physical Activity and Sedentary Time Across Retirement Transition as a Predictor of Self-Rated Health.

BACKGROUND: Retirement transition has been shown to associate with changes in physical activity (PA) and self-rated health (SRH), but their interrelationship is less studied. The aim was to investigate changes in accelerometer-measured total PA, moderate to vigorous PA (MVPA), and sedentary time across retirement transition as a predictor of SRH. METHODS: Data from the Swedish Retirement Study and the Finnish Retirement and Aging study were harmonized and pooled. Data from 3 waves (about 12 mo apart) were included: 1 preretirement (wave 1) and 2 postretirement follow-ups (wave 2-3). A totally of 245 participants (27% men) were included. Thigh-worn accelerometers were used to collect data for PA variables (wave 1-2), and SRH was obtained from the questionnaire (wave 1-3). RESULTS: Between wave 1 and 2, total PA decreased with 11 (CI, -22 to -1) minutes per day, MVPA was stable (0 [CI, -3 to 3] min), and sedentary time decreased nonsignificantly with 9 (CI, -20 to 1) minutes. SRH changed between all 3 waves (all P < .001). At preretirement, 10 more minutes of MVPA was associated with greater odds of better SRH when adjusting for accelerometer wear-time, cohort, sex, age, and occupational status (odds ratio: 1.11 [95% CI, 1.02-1.22]). This association was no longer statistically significant when additionally adjusting for marital status, body mass index, and smoking. No significant associations were observed between changes in the PA variables during retirement transition and SRH at postretirement follow-ups. CONCLUSIONS: This study showed a cross-sectional association between MVPA and greater odds of reporting better SRH before retirement. No longitudinal associations were observed between changes in the PA variables from before to after retirement and later changes in SRH.

Cohort study on incidence of new-onset type 2 diabetes in patients after bariatric surgery and matched controls.

BACKGROUND: Metabolic bariatric surgery the reduces risk of new-onset type 2 diabetes in individuals with obesity, but it is unclear whether the benefit varies by sex, age, or socioeconomic status. The aim was to assess the risk of new-onset type 2 diabetes after metabolic bariatric surgery in these subgroups. METHODS: The Finnish Public Sector study, a follow-up study with matched controls nested in a large employee cohort, included patients without type 2 diabetes and with a diagnosis of obesity or self-reported BMI of at least 35 kg/m2. For each patient who had laparoscopic metabolic bariatric surgery (2008-2016), two propensity-score matched controls were selected. New-onset type 2 diabetes was ascertained from linked records from national health registries. RESULTS: The study included a total of 917 patients and 1811 matched controls with obesity. New-onset type 2 diabetes was diagnosed in 15 of the patients who had metabolic bariatric surgery (4.1 per 1000 person-years) and 164 controls (20.2 per 1000 person-years). The corresponding rate ratio (RR) was 0.20 (95% c.i. 0.12 to 0.35) and the rate difference (RD) was -16.1 (-19.8 to -12.3) per 1000 person-years. The risk reduction was more marked in individuals of low socioeconomic status (RR 0.10 (0.04 to 0.26) and RD -20.6 (-25.6 to -15.5) per 1000 person-years) than in those with higher socioeconomic status (RR 0.35 (0.18 to 0.66) and RD -11.5 (-16.9 to -6.0) per 1000 person-years) (Pinteraction = 0.017). No differences were observed between sexes or age groups. CONCLUSION: Metabolic bariatric surgery was associated with a reduced risk of new-onset type 2 diabetes in men and women and in all age groups. The greatest benefit was observed in individuals of low socioeconomic status.

Metabolic bariatric surgery reduces the risk of new-onset type 2 diabetes in individuals with obesity or severe obesity. The risk of new-onset type 2 diabetes after metabolic bariatric surgery varies between socioeconomic status subgroups. In this prospective study, new-onset type 2 diabetes occurred in 1.6% of 917 patients who underwent metabolic bariatric surgery and 9.1% of 1811 propensity score-matched controls. Risk reduction was more marked in individuals of low socioeconomic status. There were no differences between sex or age groups. The reduced risk of new-onset type 2 diabetes after metabolic bariatric surgery emphasizes the need to increase access to treatment in patients with severe obesity. As the preventive effect was most pronounced in individuals of low socioeconomic status associated with both greater burden of disease and worse access to healthcare, the findings need to be taken into account in health policies to reduce health inequalities.

Associations between arterial health and sexual function in women aged 60-64 years.

INTRODUCTION: Female sexual dysfunction is very common, but its determinants remain under-investigated. Vasculogenic impairments are suggested to be related to female sexual dysfunction, but previous literature regarding the association is scarce. This study aims to study the association between arterial health and female sexual function in women in their 60s. MATERIAL AND METHODS: The sample for this cross-sectional study comprised 117 women (aged 60-64 years) who participated in the Finnish Retirement and Aging study. Arterial health was measured according to the participants' pulse wave velocity, ankle-brachial index, blood pressure, and pulse pressure. Sexual function was measured using the Female Sexual Function Index, which resulted in a total score and six sub-scores. Associations were examined using multivariable regression analyses, which were adjusted for age, relationship happiness, systemic menopausal hormone therapy and/or local estrogen, smoking, alcohol risk use, body mass index, and depressive symptoms. RESULTS: Higher diastolic blood pressure was associated with a higher total Female Sexual Function Index score (ß = 0.24, 95% confidence interval [CI] 0.07-0.41) and with higher desire (ß = 0.02, 95% CI 0.01-0.04), arousal (ß = 0.04, 95% CI 0.01-0.08), lubrication (ß = 0.04, 95% CI 0.002-0.08), satisfaction (ß = 0.03, 95% CI 0.003-0.05), and pain (ß = 0.06, 95% CI 0.02-0.10) sub-scores. Also, higher ankle-brachial index was associated with higher satisfaction sub-score (ß = 2.10, 95% CI 0.44-3.73) and lower pulse pressure was associated with higher orgasm sub-score (ß = 0.03, 95% CI 0.0002-0.06). Other associations between ankle-brachial index and Female Sexual Function Index scores were statistically insignificant, but considering the magnitude the findings may imply clinical significance. Systolic blood pressure and pulse wave velocity were not associated with sexual function. CONCLUSIONS: This study suggested a plausible association between higher diastolic blood pressure and female sexual function, but considering clinical significance our findings suggest an association between higher ankle-brachial index and good sexual function in women in their 60s.

Pertrochanteric hip fracture is associated with mobility decline and poorer physical performance 4 to 6 months post-hip fracture.

BACKGROUND: To study the effect of hip fracture type on physical performance, functional ability and change in mobility four to six months after the injury. METHODS: A total of 1331 patients out of consecutive 2052 patients aged ≥ 65 years who underwent hip fracture surgery were included in the study. Patient information was collected on admission, during hospitalization, by phone interview and at the geriatric outpatient clinic 4 to 6 months after the fracture. Of the 1331 eligible patients, Grip strength, Timed Up and Go -test (TUG), Elderly Mobility Scale (EMS), mobility change compared to pre-fracture mobility level, Basic Activities of Daily Living (BADL) and Instrumental Activities of Daily Living (IADL) were used to determine physical performance and functional ability. Logistic regression was used for the analyses which was adjusted for gender, age, American Society of Anesthesiologists score, diagnosis of cognitive disorder, pre-fracture living arrangements, mobility and need of mobility aid. RESULTS: Patients with pertrochanteric hip fracture had an EMS lower than 14 (Odds Ratio (OR) 1.38, 95% confidence intervals (CI) 1.00-1.90), TUG time ≥ 20 s (OR 1.69, 95% CI 1.22-2.33) and they had declined in mobility (OR 1.58, 95% CI 1.20-2.09) compared to femoral neck fracture patients 4 to 6 months post-hip fracture in multivariable-adjusted logistic regression analyses. Grip strength and functional ability (IADL, BADL) 4 to 6 months after hip fracture did not differ between fracture types. There were no statistically significant differences in physical performance in patients with a subtrochanteric fracture compared to patients with a femoral neck fracture. CONCLUSIONS: Pertrochanteric hip fracture independently associated with poorer physical performance 4 to 6 months post hip fracture compared to other hip fracture types. Pertrochanteric hip fracture patients should be given special attention in terms of regaining their previous level of mobility.

Concurrent changes in physical activity and physical functioning during retirement transition-a multi-trajectory analysis.

BACKGROUND: Physical activity and physical functioning have been reported to change over retirement transition, but the results have been inconsistent, and the two constructs have not been studied concurrently. The objective of this study was to examine concurrent changes in physical activity and physical functioning during transition to retirement among public sector employees, and to examine if occupation, sex, marital status, body mass index (BMI), alcohol consumption and smoking status are associated with observed different multi-trajectory paths. METHODS: 3,550 participants of the Finnish Retirement and Aging study responded to an annual survey on physical activity and physical functioning (SF-36) before and after retirement. Group-based multi-trajectory analysis was used to identify clusters with dissimilar concurrent changes in physical activity and physical functioning. Multinomial regression analysis was used to describe the associations between covariates and the probability of being classified to a certain cluster. RESULTS: Participants were 63.4 (SD 1.4) years old, 83% women, 65% professional workers. Four trajectories of concurrent changes in physical activity and physical functioning were identified, one with decreasing physical functioning and low activity, one with increasing high activity and stable high functioning and two with fluctuating moderate physical activity and stable high functioning. Single, women, obese participants and risk-users of alcohol were more likely to be classified into group with low physical activity and declining physical functioning. CONCLUSIONS: Low physical activity below the level usually recommended was associated with lower physical functioning during retirement transition. These findings could be useful when planning interventions for retirees to maintain their physical functioning level.

Physical activity and self-rated health during retirement transition: a multitrajectory analysis of concurrent changes among public sector employees.

OBJECTIVES: The aim of the study was to evaluate concurrent changes in physical activity and self-rated health during retirement transition over 4 years by multivariate trajectory analysis and to examine whether sociodemographic and lifestyle factors predict the probability of being classified to a certain subgroup of observed changes. DESIGN: Prospective cohort study. SETTING: Public sector employees. PARTICIPANTS: 3550 participants of the Finnish Retirement and Aging study. PRIMARY AND SECONDARY OUTCOME MEASURES: Participants estimated on a yearly questionnaire their weekly hours of different types of activities converted to metabolic equivalent of task-hour/week. Self-rated health was assessed on a 5-point Likert-like scale from poor to excellent and dichotomised as suboptimal and optimal. Multivariate trajectory analysis was used to distinguish different subgroups of trajectories. Multinomial regression analysis was used to describe the associations between covariates and the probability of being classified to a certain trajectory group. RESULTS: Three trajectory groups were identified, all displaying increasing activity during retirement with a simultaneous decrease in perceived suboptimal health. Physical activity peaked at 18 months after retirement and then slightly decreased, except for initially highly physically active participants (9%) with good self-rated health, who demonstrated a constant high level of physical activity. Male gender, professional occupation, being married or cohabiting, body mass index <30 kg/m2, not smoking and using alcohol below risk levels were associated with higher physical activity and better self-rated health. CONCLUSION: Changes in physical activity and perceived health during retirement transition were interconnected. Both were improved during retirement transition, but the change was temporary. Longer follow-up studies are required to assess the changes over a longer period after retirement.

Daily Physical Activity Patterns and Their Associations with Cardiometabolic Biomarkers: The Maastricht Study.

PURPOSE: This study aimed to identify physical activity patterns and examine their association with cardiometabolic biomarkers in a cross-sectional design. METHODS: Overall 6072 participants (mean age, 60.2 yr; SD 8.6 yr, 50% women) from The Maastricht Study provided daily physical activity data collected with thigh-worn activPAL3 accelerometers. The patterns of daily physical activity over weekdays and weekend days were identified by using Group Based Trajectory Modeling. Cardiometabolic biomarkers included body mass index, waist circumference, office blood pressure, glucose, HbA1c, and cholesterol levels. Associations between the physical activity patterns and cardiometabolic outcomes were examined using the analyses of covariance adjusted for sex, age, education, smoking, and diet. Because of statistically significant interaction, the analyses were stratified by type 2 diabetes status. RESULTS: Overall, seven physical activity patterns were identified: consistently inactive (21% of participants), consistently low active (41%), active on weekdays (15%), early birds (2%), consistently moderately active (7%), weekend warriors (8%), and consistently highly active (6%). The consistently inactive and low active patterns had higher body mass index, waist, and glucose levels compared with the consistently moderately and highly active patterns, and these associations were more pronounced for participants with type 2 diabetes. The more irregular patterns accumulated moderate daily total activity levels but had rather similar cardiometabolic profiles compared with the consistently active groups. CONCLUSIONS: The cardiometabolic profile was most favorable in the consistently highly active group. All patterns accumulating moderate to high levels of daily total physical activity had similar health profile suggesting that the amount of daily physical activity rather than the pattern is more important for cardiometabolic health.

Probable Sarcopenia, Obesity, and Risk of All-Cause Mortality: A Pooled Analysis of 4,612 Participants.

INTRODUCTION: Conflicting evidence exists concerning whether having sarcopenic obesity has additive mortality risk over having only sarcopenia or obesity. We examined the independent and combined associations of obesity and probable sarcopenia with all-cause mortality. METHODS: The pooled analysis included three large, harmonized datasets (Health 2000 Survey; Health, Aging and Body Composition Study; Longitudinal Aging Study Amsterdam) with mortality follow-up data on individuals aged 70 years and over at baseline (n = 4,612). Obesity indicators included body mass index and waist circumference, and probable sarcopenia was defined based on grip strength. The mixed effects Cox model was used for statistical analyses, adjusting for age, sex, marital status, education, race, physical activity, alcohol consumption, smoking, and baseline diseases. RESULTS: Risk of death increased for those having probable sarcopenia only (hazard ratio [HR]: 1.61, 95% confidence interval [CI]: 1.39-1.85) or probable sarcopenia with obesity (HR: 1.36, 95% CI: 1.13-1.64) but not for the obese-only group (HR: 0.92, 95% CI: 0.85-1.01), when compared to non-obese non-sarcopenic individuals. The results were similar regardless of adjustments for covariates or different obesity criteria applied. CONCLUSION: Probable sarcopenia, whether combined with obesity or not, is associated with increased mortality. Obesity did not increase mortality among older adults. Maintaining muscle strength and identifying older adults at risk of sarcopenia is important for the prevention of premature mortality.

Circulating cell-free DNA in health and disease - the relationship to health behaviours, ageing phenotypes and metabolomics.

Circulating cell-free DNA (cf-DNA) has emerged as a promising biomarker of ageing, tissue damage and cellular stress. However, less is known about health behaviours, ageing phenotypes and metabolic processes that lead to elevated cf-DNA levels. We sought to analyse the relationship of circulating cf-DNA level to age, sex, smoking, physical activity, vegetable consumption, ageing phenotypes (physical functioning, the number of diseases, frailty) and an extensive panel of biomarkers including blood and urine metabolites and inflammatory markers in three human cohorts (N = 5385; 17-82 years). The relationships were assessed using correlation statistics, and linear and penalised regressions (the Lasso), also stratified by sex.cf-DNA levels were significantly higher in men than in women, and especially in middle-aged men and women who smoke, and in older more frail individuals. Correlation statistics of biomarker data showed that cf-DNA level was higher with elevated inflammation (C-reactive protein, interleukin-6), and higher levels of homocysteine, and proportion of red blood cells and lower levels of ascorbic acid. Inflammation (C-reactive protein, glycoprotein acetylation), amino acids (isoleucine, leucine, tyrosine), and ketogenesis (3-hydroxybutyrate) were included in the cf-DNA level-related biomarker profiles in at least two of the cohorts.In conclusion, circulating cf-DNA level is different by sex, and related to health behaviour, health decline and metabolic processes common in health and disease. These results can inform future studies where epidemiological and biological pathways of cf-DNA are to be analysed in details, and for studies evaluating cf-DNA as a potential clinical marker.

Association of alcohol use with years lived without major chronic diseases: A multicohort study from the IPD-Work consortium and UK Biobank.

Background: Heavy alcohol consumption increases the risk of several chronic diseases. In this multicohort study, we estimated the number of life-years without major chronic diseases according to different characteristics of alcohol use. Methods: In primary analysis, we pooled individual-level data from up to 129,942 adults across 12 cohort studies with baseline data collection on alcohol consumption, drinking patterns, and history between 1986 and 2005 (the IPD-Work Consortium). Self-reported alcohol consumption was categorised according to UK guidelines - non-drinking (never or former drinkers); moderate consumption (1-14 units); heavy consumption (>14 units per week). We further subdivided moderate and heavy drinkers by binge drinking pattern (alcohol-induced loss of consciousness). In addition, we assessed problem drinking using linked data on hospitalisations due to alcohol abuse or poisoning. Follow-up for chronic diseases for all participants included incident type 2 diabetes, coronary heart disease, stroke, cancer, and respiratory disease (asthma and chronic obstructive pulmonary disease) as ascertained via linkage to national morbidity and mortality registries, repeated medical examinations, and/or self-report. We estimated years lived without any of these diseases between 40 and 75 years of age according to sex and characteristics of alcohol use. We repeated the main analyses using data from 427,621 participants in the UK Biobank cohort study. Findings: During 1·73 million person-years at risk, 22,676 participants in IPD-Work cohorts developed at least one chronic condition. From age 40 to 75 years, never-drinkers [men: 29·3 (95%CI 27·9-30·8) years, women 29·8 (29·2-30·4) years)] and moderate drinkers with no binge drinking habit [men 28·7 (28·4-29·0) years, women 29·6 (29·4-29·7) years] had the longest disease-free life span. A much shorter disease-free life span was apparent in participants who experienced alcohol poisoning [men 23·4 (20·9-26·0) years, women 24·0 (21·4-26·5) years] and those with self-reported heavy overall consumption and binge drinking [men: 26·0 (25·3-26·8), women 27·5 (26·4-28·5) years]. The pattern of results for alcohol poisoning and self-reported alcohol consumption was similar in UK Biobank. In IPD-Work and UK Biobank, differences in disease-free years between self-reported moderate drinkers and heavy drinkers were 1·5 years or less. Interpretation: Individuals with alcohol poisonings or heavy self-reported overall consumption combined with a binge drinking habit have a marked 3- to 6-year loss in healthy longevity. Differences in disease-free life between categories of self-reported weekly alcohol consumption were smaller. Funding: Medical Research Council, National Institute on Aging, NordForsk, Academy of Finland, Finnish Work Environment Fund.

Comparison of Oura Smart Ring Against ActiGraph Accelerometer for Measurement of Physical Activity and Sedentary Time in a Free-Living Context.

Smart rings, such as the Oura ring, might have potential in health monitoring. To be able to identify optimal devices for healthcare settings, validity studies are needed. The aim of this study was to compare the Oura smart ring estimates of steps and sedentary time with data from the ActiGraph accelerometer in a free-living context. A cross-sectional observational study design was used. A convenience sample of healthy adults (n = 42) participated in the study and wore an Oura smart ring and an ActiGraph accelerometer on the non-dominant hand continuously for 1 week. The participants completed a background questionnaire and filled out a daily log about their sleeping times and times when they did not wear the devices. The median age of the participants (n = 42) was 32 years (range, 18-46 years). In total, 191 (61% of the potential) days were compared. The Oura ring overestimated the step counts compared with the ActiGraph. The mean difference was 1416 steps (95% confidence interval, 739-2093 steps). Daily sedentary time was also overestimated by the ring; the mean difference was 17 minutes (95% confidence interval, -2 to 37 minutes). The use of the ring in nursing interventions needs to be considered.

Persistence of sleep difficulties for over 16 years amongst 66,948 working-aged adults.

The objective was to investigate the persistence of sleep difficulties for over 16 years amongst a population of working age. In this prospective cohort study, a group-based trajectory analysis of repeated surveys amongst 66,948 employees in public sector (mean age 44.7 [SD 9.4] years, 80% women) was employed. The main outcome measure was sleep difficulties based on Jenkins Sleep Scale (JSS). Up to 70% of the respondents did not experience sleep difficulties whereas up to 4% reported high frequency of notable sleep difficulties through the entire 16-year follow-up. Heavy drinking predicted sleep difficulties (OR 2.3 95% CI 1.6 to 3.3) except for the respondents younger than 40 years. Smoking was associated with sleep difficulties amongst women younger than 40 years (OR 1.2, 95% CI 1.0 to 1.5). Obesity was associated with sleep difficulties amongst men (OR 1.9, 95% CI 1.4 to 2.7) and women (OR 1.2, 95% CI 1.1 to 1.3) of middle age and amongst women older than 50 (OR 1.5, 95% CI 1.2 to 1.8) years. Physical inactivity predicted sleep difficulties amongst older men (OR 1.3, 95% CI 1.1 to 1.6). In this working-age population, sleep difficulties showed a great persistence over time. In most of the groups, the level of sleep difficulties during the follow-up was almost solely dependent on the level of initial severity. Depending on sex and age, increasing sleep problems were sometimes associated with high alcohol consumption, smoking, obesity and physical inactivity, but the strength of these associations varied.

Daily Physical Activity Patterns and Their Association With Health-Related Physical Fitness Among Aging Workers-The Finnish Retirement and Aging Study.

BACKGROUND: This study aimed to identify accelerometer-measured daily physical activity patterns, and to examine how they associate with health-related physical fitness among aging workers. METHODS: The study population consisted of 263 participants (mean age 62.4 years, SD 1.0) from the Finnish Retirement and Aging study, who used wrist-worn ActiGraph accelerometer for at least 1 week including both workdays and days off. Health-related physical fitness measures included body composition (waist circumference, bioimpedance), cardiorespiratory fitness (bicycle ergometer test), and muscular fitness (push-up and chair rise tests). RESULTS: Based on the latent class trajectory analysis, 6 trajectories were identified for workdays showing variation in activity level on working hours and on evening hours. Moderate activity during working hours and increase of activity level in the evening was associated with the most favorable health-related fitness in comparison to low activity throughout the workday: waist circumference 90.0 cm (95% confidence interval [CI] 85.5-94.5) versus 99.5 cm (95% CI 96.8-102.3), fat mass 13.9 kg (9.3-18.5) versus 23.8 kg (20.2-27.4), cardiorespiratory fitness 33.4 mL/kg/min (95% CI 31.4-35.3) versus 29.1 mL/kg/min (95% CI 27.8-30.3) (adjusted for age, sex, days off activity, smoking, and alcohol). For the days off, 2 different trajectories were identified, but they differed only in terms of level and not by timing of physical activity. CONCLUSIONS: A large variation in the workday physical activity patterns was observed among aging workers. Independent of worktime activity, people who were more active in the evenings had more favorable health-related physical fitness than those who were less active throughout the day.

Association of Healthy Lifestyle With Years Lived Without Major Chronic Diseases.

Importance: It is well established that selected lifestyle factors are individually associated with lower risk of chronic diseases, but how combinations of these factors are associated with disease-free life-years is unknown. Objective: To estimate the association between healthy lifestyle and the number of disease-free life-years. Design, Setting, and Participants: A prospective multicohort study, including 12 European studies as part of the Individual-Participant-Data Meta-analysis in Working Populations Consortium, was performed. Participants included 116 043 people free of major noncommunicable disease at baseline from August 7, 1991, to May 31, 2006. Data analysis was conducted from May 22, 2018, to January 21, 2020. Exposures: Four baseline lifestyle factors (smoking, body mass index, physical activity, and alcohol consumption) were each allocated a score based on risk status: optimal (2 points), intermediate (1 point), or poor (0 points) resulting in an aggregated lifestyle score ranging from 0 (worst) to 8 (best). Sixteen lifestyle profiles were constructed from combinations of these risk factors. Main Outcomes and Measures: The number of years between ages 40 and 75 years without chronic disease, including type 2 diabetes, coronary heart disease, stroke, cancer, asthma, and chronic obstructive pulmonary disease. Results: Of the 116 043 people included in the analysis, the mean (SD) age was 43.7 (10.1) years and 70 911 were women (61.1%). During 1.45 million person-years at risk (mean follow-up, 12.5 years; range, 4.9-18.6 years), 17 383 participants developed at least 1 chronic disease. There was a linear association between overall healthy lifestyle score and the number of disease-free years, such that a 1-point improvement in the score was associated with an increase of 0.96 (95% CI, 0.83-1.08) disease-free years in men and 0.89 (95% CI, 0.75-1.02) years in women. Comparing the best lifestyle score with the worst lifestyle score was associated with 9.9 (95% CI 6.7-13.1) additional years without chronic diseases in men and 9.4 (95% CI 5.4-13.3) additional years in women (P < .001 for dose-response). All of the 4 lifestyle profiles that were associated with the highest number of disease-free years included a body-mass index less than 25 (calculated as weight in kilograms divided by height in meters squared) and at least 2 of the following factors: never smoking, physical activity, and moderate alcohol consumption. Participants with 1 of these lifestyle profiles reached age 70.3 (95% CI, 69.9-70.8) to 71.4 (95% CI, 70.9-72.0) years disease free depending on the profile and sex. Conclusions and Relevance: In this multicohort analysis, various healthy lifestyle profiles appeared to be associated with gains in life-years without major chronic diseases.

Excess body weight, cigarette smoking, and type II diabetes incidence in the national FINRISK studies.

PURPOSE: We identify the individual and joint contributions of excess weight and cigarette smoking to national-level type II diabetes (T2D) incidence and to educational and gender disparities therein filling an important gap in T2D epidemiology. METHODS: Based on the FINRISK surveys conducted in 1997, 2002, and 2007 and linked to the Finnish National Drug Reimbursement Register through 2011, we used a regression-counterfactual approach to estimate the percentage of diagnosed drug-treated incident T2D cases attributable to excess body weight and cigarette smoking. Body mass index (BMI) and waist circumference were evaluated. RESULTS: T2D incidence was 10.24 in men and 7.04 in women per 1000 person-years. Excess baseline BMI (≥25.0 kg/m2) explained 69% and 63%, and smoking explained 9% and 14% of T2D incidence, in men and women, respectively. Most of the gender difference was explained by the risk factors. Approximately 90% in men and 98% in women of the higher T2D incidence among those in the lower versus upper third of the educational distribution was explained by excess BMI. The results were similar for waist circumference and lifetime maximum BMI. CONCLUSIONS: Excess body weight is the main risk factor contributing to national-level T2D incidence and disparities by educational attainment and gender in a high-income population.

Association between socioeconomic status and the development of mental and physical health conditions in adulthood: a multi-cohort study.

BACKGROUND: Socioeconomic disadvantage is a risk factor for many diseases. We characterised cascades of these conditions by using a data-driven approach to examine the association between socioeconomic status and temporal sequences in the development of 56 common diseases and health conditions. METHODS: In this multi-cohort study, we used data from two Finnish prospective cohort studies: the Health and Social Support study and the Finnish Public Sector study. Our pooled prospective primary analysis data comprised 109 246 Finnish adults aged 17-77 years at study entry. We captured socioeconomic status using area deprivation and education at baseline (1998-2013). Participants were followed up for health conditions diagnosed according to the WHO International Classification of Diseases until 2016 using linkage to national health records. We tested the generalisability of our findings with an independent UK cohort study-the Whitehall II study (9838 people, baseline in 1997, follow-up to 2017)-using a further socioeconomic status indicator, occupational position. FINDINGS: During 1 110 831 person-years at risk, we recorded 245 573 hospitalisations in the Finnish cohorts; the corresponding numbers in the UK study were 60 946 hospitalisations in 186 572 person-years. Across the three socioeconomic position indicators and after adjustment for lifestyle factors, compared with more advantaged groups, low socioeconomic status was associated with increased risk for 18 (32·1%) of the 56 conditions. 16 diseases formed a cascade of inter-related health conditions with a hazard ratio greater than 5. This sequence began with psychiatric disorders, substance abuse, and self-harm, which were associated with later liver and renal diseases, ischaemic heart disease, cerebral infarction, chronic obstructive bronchitis, lung cancer, and dementia. INTERPRETATION: Our findings highlight the importance of mental health and behavioural problems in setting in motion the development of a range of socioeconomically patterned physical illnesses. Policy and health-care practice addressing psychological health issues in social context and early in the life course could be effective strategies for reducing health inequalities. FUNDING: UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science.

Diet quality as a predictor of cardiometabolic disease-free life expectancy: the Whitehall II cohort study.

BACKGROUND: Poor diet quality has been linked to increased risk of many chronic diseases and premature mortality. Less research has considered dietary habits in relation to disease-free life expectancy. OBJECTIVES: Our objective was to investigate the association of diet quality with cardiometabolic disease-free life expectancy between ages 50 and 85 y. METHODS: Diet quality of 8041 participants of the Whitehall II cohort study was assessed with the Alternative Healthy Eating Index 2010 (AHEI-2010) in 1991-1994, 1997-1999, and 2002-2004. The measurement of diet quality closest to age 50 for each participant was used. We utilized repeat measures of cardiometabolic disease (coronary heart disease, stroke, and type 2 diabetes) from the first observation when participants were aged ≥50 y. Multistate life table models with covariates age, gender, occupational position, smoking, physical activity, and alcohol consumption were used to estimate total and sex-specific cardiometabolic disease-free life expectancy from age 50 to 85 y for each AHEI-2010 quintile, where the lowest quintile represents unhealthiest dietary habits and the highest quintile the healthiest habits. RESULTS: The number of cardiometabolic disease-free life-years after age 50 was 23.9 y (95% CI: 23.0, 24.9 y) for participants with the healthiest diet, that is, a higher score on the AHEI-2010, and 21.4 y (95% CI: 20.6, 22.3 y) for participants with the unhealthiest diet. The association between diet quality and cardiometabolic disease-free life expectancy followed a dose-response pattern and was observed in subgroups of participants of different occupational position, BMI, physical activity level, and smoking habit, as well as when participants without cardiometabolic disease at baseline were excluded from analyses. CONCLUSIONS: Healthier dietary habits are associated with cardiometabolic disease-free life expectancy between ages 50 and 85.

Commuting time to work and behaviour-related health: a fixed-effect analysis.

OBJECTIVES: Long commuting times are linked to poor health outcomes, but the evidence is mainly cross-sectional. We examined longitudinal within-individual associations between commuting time and behaviour-related health. METHODS: Data were from the Swedish Longitudinal Occupational Survey of Health study. We selected workers who responded to a minimum of two surveys conducted every other year between 2008 and 2018. We included all study waves with self-reported commuting time (ie, the exposure, 1-5, 6-10, 11-15 or ≥15 hours/week), body mass index (based on weight and height), physical (in)activity, smoking, alcohol use and sleep problems (ie, the outcomes) (Nindividuals=20 376, Nobservations=46 169). We used conditional logistic regression for fixed effects analyses that controls for time-varying confounders by design. Analyses were stratified by working hours: normal (30-40 hours/week) or longer than normal (>40 hours/week) and adjusted for time dependent covariates: age, marital status, occupational position, presence of children, chronic disease, depressive symptoms, job strain and shift work. RESULTS: Those working >40 hours/week had higher odds of physical inactivity (OR 1.25, 95% CI 1.03 to 1.51) and sleep problems (OR 1.16, 95% CI 1.00 to 1.35) when they were commuting >5 hours/week than when they were commuting 1-5 hours/week. Among women working normal hours, longer commuting time associated with lower odds of problem drinking. CONCLUSION: Our findings suggest that lengthy commuting time increases the risk of physical inactivity and sleep problems if individuals have longer than normal weekly working hours. Effects of work arrangements that decrease commuting time should be examined in relation to health behaviours.

Projecting long-term trends in mobility limitations: impact of excess weight, smoking and physical inactivity.

BACKGROUND: Policy makers need disability projections for planning adequate services and measures for health promotion. The aim of this study is to provide projections on severe mobility limitations up to year 2044 and illustrate how the projected prevalence and the number of persons with severe mobility limitations are affected by potential changes in the modifiable risk factors, namely excess weight, physical inactivity and smoking. METHODS: We analysed the nationally representative, repeated measures Health 2000 and 2011 Surveys (BRIF8901) with 8615 and 6740 participants, respectively, aged 18 years and older. Severe mobility limitations were defined as major difficulties or unable to walk about half a kilometre. We applied a multistate model on repeated measures to account for both individual risk factors and their changes over time. RESULTS: The number of people with severe mobility limitations was projected to double by the year 2044 in Finland, due to the rapid ageing of the population. Eliminating half of the excess weight would reduce their number by one-fifth, while reductions in the prevalence of smoking and physical inactivity would have a minor impact. Even if excess weight, smoking and physical inactivity were completely eliminated, the number of persons with severe mobility limitations is projected to increase. CONCLUSIONS: Designing and implementing strategies to promote healthy weight are important to slow down the rapid increase in mobility limitations due to population ageing. Providing adequate health and social services for the increasing population with disabilities will nevertheless be an increasing national challenge.

Socioeconomic differences in healthy and disease-free life expectancy between ages 50 and 75: a multi-cohort study.

BACKGROUND: There are striking socioeconomic differences in life expectancy, but less is known about inequalities in healthy life expectancy and disease-free life expectancy. We estimated socioeconomic differences in health expectancies in four studies in England, Finland, France and Sweden. METHODS: We estimated socioeconomic differences in health expectancies using data drawn from repeated waves of the four cohorts for two indicators: (i) self-rated health and (ii) chronic diseases (cardiovascular, cancer, respiratory and diabetes). Socioeconomic position was measured by occupational position. Multistate life table models were used to estimate healthy and chronic disease-free life expectancy from ages 50 to 75. RESULTS: In all cohorts, we found inequalities in healthy life expectancy according to socioeconomic position. In England, both women and men in the higher positions could expect 82-83% of their life between ages 50 and 75 to be in good health compared to 68% for those in lower positions. The figures were 75% compared to 47-50% for Finland; 85-87% compared to 77-79% for France and 80-83% compared to 72-75% for Sweden. Those in higher occupational positions could expect more years in good health (2.1-6.8 years) and without chronic diseases (0.5-2.3 years) from ages 50 to 75. CONCLUSION: There are inequalities in healthy life expectancy between ages 50 and 75 according to occupational position. These results suggest that reducing socioeconomic inequalities would make an important contribution to extending healthy life expectancy and disease-free life expectancy.